updateConnectionUpdate an existing connection. For sensitive header values, sending an empty string keeps the existing value; send a new value to overwrite. Toggling shared moves the connection between personal and team-shared.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | ||
| shared | No | ||
| headers | No | ||
| server_url | No | ||
| auth_method | No | ||
| connection_id | Yes | Connection ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations: it explains the empty-string semantics for sensitive header values (keep existing vs. overwrite) and the effect of toggling 'shared' (moving between personal and team-shared). These are non-obvious behaviors that the schema alone doesn't convey. Annotations only provide basic hints (readOnlyHint=false, etc.), so the description carries significant weight and handles it well, though it could mention permissions or reversibility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each delivering essential information: the core action and two key behavioral nuances. It is front-loaded with the purpose and contains no filler. Every word earns its place, making it a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 6 parameters and no output schema, the description provides some crucial behavior (header handling, shared toggling) but omits other important context: what happens to unspecified fields (presumably unchanged), whether any fields are conditionally required, or the expected response format. With no output schema and sparse annotations, a more complete description would improve safety and correctness. The provided details are useful but not sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is only 17% (only connection_id has a description), so the description must compensate. It does explain the semantics of 'headers' (empty-string behavior) and 'shared' (toggling effect), which are clearly useful. However, it leaves other fields (name, server_url, auth_method) undefined, and the nested structure of headers (secret/plaintext) is not described. This is partial compensation for a low-coverage schema, but not complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Update an existing connection,' a specific verb+resource statement that clearly identifies the tool's function. It distinguishes from siblings like createConnection and deleteConnection by focusing on updating, and the resource is unambiguous. Though it doesn't name specific sibling tools, the scope is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided about when to use this tool versus alternatives (e.g., createConnection, deleteConnection). The intended usage is implied by the tool name and 'existing connection,' but the description gives no context, exclusions, or alternative recommendations. This falls under 'no guidance' rather than 'implied usage' because it doesn't even mention prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Despite detailed descriptions, many tool names are highly ambiguous, with multiple tools covering the same conceptual actions (e.g., acceptClarityCaptureSuggestion vs. acceptClarityTeamAssignmentSuggestion, or the many deleteClarity*Interview tools). The set is so large that distinguishing between, say, listClarityFolders, listClarityProcesses, and listClarityProcessSummaries requires reading deep into descriptions, reducing agent selection accuracy.
The naming convention is predominantly verb_noun (e.g., createClarityProcess, listAgents, deleteQueue), and is remarkably consistent across the 316 tools. There are only minor deviations, such as 'fileSuggestedClarityProcesses' (verb + adjective noun) and 'bulkUpdateCasePriority' (where 'bulk' could be seen as a prefix), but overall the pattern holds strongly.
With 316 tools, this server is extremely oversized for any single agent to manage effectively. The massive number of tools suggests poor modularization—many of these tools likely belong in separate, smaller servers focused on specific domains (e.g., Clarity, Pulse, Agent management). The cognitive load for an agent to choose from 316 options is very high, leading to frequent misselection.
The tool surface covers an extraordinarily wide range of operations across the Duvo platform: agents, runs, cases, queues, Clarity processes, skills, integrations, notifications, teams, and more. Most resource types have full CRUD and lifecycle management. Notable minor gaps exist (e.g., no tools for managing specific notification batch severities dynamically, and some interview management is missing batch operations), but for the platform's scope, coverage is impressively thorough.